Nina Schiettekatte of PSL Research University takes us on a journey to French Polynesia to discuss her 2020 Haldane Prize shortlisted work “Nutrient limitation, bioenergetics and stoichiometry: A new model to predict elemental fluxes mediated by fishes” – and the joy of R!
The ocean has always piqued my curiosity, and I am drawn to any large body of water. Following my undergraduate studies in biology in Ghent, Belgium, I enrolled in the Erasmus Mundus Master of Science in marine biodiversity and conservation, which allowed me to continue my studies across three European universities. In addition, during my Master’s degree, I was lucky to discover the beauty of coral reef ecosystems by participating in research in the Philippines and Australia. As soon as I put on my mask, I fell in love with coral reef fishes – I wanted to know where they go, what they eat, and how they interact. Soon after my exposure to coral reef science, I started my PhD in southern France, focusing on the role of coral reef fishes in elemental cycling.
At the start of my PhD journey, I sought to use existing bioenergetic models to predict the rate of nutrient excretion by fishes and ultimately quantify community-level nutrient fluxes. As I further delved into the topic, I realized that existing models counterintuitively predicted negative excretion rates for fishes that feed on low-nutrient diets such as algae or detritus. How was this possible? Bioenergetic models typically assume fishes are limited by energy (carbon), but we know that some fishes can be limited by nitrogen or phosphorus instead. Thus, I concluded that existing models were not appropriate for a wide range fishes, and I decided to create a new model that includes carbon, nitrogen, and phosphorus limitation depending on the needs of fishes. The creation of this model resulted in my first PhD paper, published in Functional Ecology, and it became the basis of much of my current work.
In many aquatic ecosystems, fishes are highly abundant and perform an important role in the cycling of elements through ingestion, growth, and excretion. In this paper, we present a new model that integrates estimates of energy requirements with the explicit consideration of either carbon, nitrogen, or phosphorus limitation. With empirically measured parameters, our model predicts elemental fluxes through ingestion, growth, excretion, respiration, and egestion, taking into account uncertainty of input parameters. We validate our approach through a case study of three reef fishes with distinct diets. Further, we show that not accounting for nutrient limitation can result in a substantial underestimation of ingestion and excretion rates. Our model improves predictions of multiple nutrient cycling processes across all fish life stages, particularly for species that experience nutrient limitation. By integrating well-defined and widely accessible parameters, we provide a user-friendly path to foster a better understanding of the role of fishes in nutrient cycling.
This research allowed me to expand my knowledge on many diverse topics, including fish physiology and stoichiometric theory. Further, I was able conduct field experiments to test my model and further develop R programming skills, which culminated in the creation of my first R package called fishflux, which makes my model user-friendly and applicable for other researchers. During this journey, I discovered the joy of creating R packages and became passionate about reproducibility in science. Since creating fishflux, I have also created fishualize, a data visualization R package that provides color palettes and fish shapes to create beautiful graphs inspired by nature’s colorful fishes.
Currently, I am completing my PhD dissertation. A portion of my research focuses on scaling up fish-mediated fluxes to the community level, which involved extensive data collection and modelling (again making use of my package fishflux). I quantified five key functions—nitrogen and phosphorus cycling, biomass production, herbivory, and piscivory—mediated by reef fish communities across the world’s tropical oceans, and unraveled their drivers, trade-offs, and vulnerabilities. In addition, I focused on the quality and quantity of coral reef fish feces, which highlighted their important role as a vector of nutrients on coral reefs. Finally, I attempted to quantify the metabolic rate of fishes in their natural environment by integrating respirometry experiments and stereo-video observations. Once I finish my PhD, I would like to continue to unravel the complexity of nature by quantifying ecosystem functions, in the hope that this may help conserving ecosystem functioning.
I love being an ecologist because when I am in the field, conducting data analysis, or brainstorming ideas with colleagues, it does not feel like work. As a young ecologist, I feel incredibly privileged to have the liberty to pursue my curiosity of the natural world. For people about to embark on a career in ecology, I would advise to shake off any feelings of inadequacy or uncertainty and follow your curiosity without restraints. A couple of years ago, I had negligible knowledge of fish physiology and programming, and never would have imagined that I could create my own R package.
In my spare time, I enjoy Harry Potter trivia, making nonsensical R packages, getting lost on hiking trails, listening to records, and having disco dance parties in my apartment (now solo, thanks to COVID).
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